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• W4313612046 abstract "In this paper a novel under-voltage load shedding approach is presented for voltage stability of power systems. Given the significance of load model on load shedding plan, in addition to adoption of a voltage-dependent load model, the total grid load is divided into discrete levels corresponding to the discrete number of feeders connected to each bus. Through demand response and designation of critical loads, the load shedding plan and costs are optimized. Using the assumptions and network characteristics and their combination, which has not been previously carried out, the load shedding problem is handled in two offline and online forms. In the offline solution, the improved discrete particle swarm optimization (IDPSO) is used. Then, by combining the IDPSO algorithm with ANN as a novelty of the proposed approach, by assessing different faults, establishing a database and neural network training tools, the proposed method is applied in the online mode on the basis of data received from network PMUs leading to very fast solutions and therefore higher margin of voltage stability. The proposed approach is implemented on an IEEE 57-bus test network and the results of both offline and online methods are discussed for different fault scenarios." @default.
• W4313612046 created "2023-01-07" @default.
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• W4313612046 date "2023-04-01" @default.
• W4313612046 modified "2023-09-26" @default.
• W4313612046 title "Real-time under-voltage load shedding method considering integer-value load model and feeder participation in demand response" @default.
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• W4313612046 doi "https://doi.org/10.1016/j.epsr.2023.109115" @default.
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